The project explores how data donation can be integrated into survey infrastructures for collecting digital trace data. It analyzes representation and measurement errors and develops strategies to mitigate biases caused by low participation rates.
The project investigates how data donation as a new method for collecting digital trace data can be integrated into survey infrastructure. Since data donation allows for detailed and longitudinal measurements of individual behavior, it can amplify data from surveys. In addition to implementing data donation in survey infrastructures from a technical perspective, the project focuses on quantifying and explaining errors in representation and measurement that arise from this integration. Furthermore, the project develops and adapts survey design strategies and statistical methods to systematically address low participation rates in surveys with integrated data donation and resulting biases. In doing so, the project draws on different types of data (survey data, digital trace data, administrative data, synthetic data) as well as samples (nonprobability samples from online access panels, probability sample from the Panel Study Labour Market and Social Security at the Institute for Employment Research).
Data Donation | Digital Trace Data | Survey Methods
Academic Staff
Computational Social Science • Digital Journalism • Crisis and Conflict Communication
The project includes several research projects within LMU. That's because it's great and very interdisciplinary.